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生成型人工智能在兽医后期研究中提供了准确的病例选择

Armen M Brus¹, Thomas Edwards^1,2, Genna Atiee¹

¹College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX.

American journal of veterinary research

|December 10, 2025

概括

人工智能 (AI) 工具,特别是Gemini 2.5 Pro,在识别用于兽医研究的病例方面表现出高准确性. 这通过匹配专家选择来加速研究,但人工智能结果需要调查人员验证.

科学领域:

兽医医学兽医医学兽医医学
医疗信息学医疗信息学
人工智能的人工智能

背景情况:

追溯的兽医研究需要根据纳入/排除标准准确确定病例.
手动审查医疗记录是耗时的,可能是研究中的瓶.

研究的目的:

评估自动化工具和专家评估人员在识别病例后期兽医研究方面的协议.
将不同AI应用程序和关键字搜索算法的性能与专家判断进行比较.

主要方法:

评估了三个研究种群 (创伤犬,支架患者,胆囊切除犬).
专家审查员将医疗记录与AI工具 (Gemini 2.5 Pro,NotebookLM) 和基于Python的关键字搜索算法进行了比较.
记录了处理时间和与专家选择的协议.

主要成果:

双子 2.5 Pro 显示了高精度 (99%-100%) 和快速处理时间,与各个研究中的专家选择密切匹配.
笔记本LM显示了对支架数据集的可比性能,但对其他数据集的准确性较低.
根据研究,Python工具表现出不同的性能.

结论:

人工智能工具,特别是像Gemini 2.5 Pro这样的生成性AI,可以有效地识别符合研究标准的案例,加速回顾性研究开发.
人工智能提高了兽医研究的速度和可扩展性,在临床实践中有潜在的应用.
在最终数据注册之前,调查人员对AI识别病例的验证至关重要.

关键词:

协议协议协议协议协议人工智能的人工智能是人工智能.案例选择的情况选择.数据分析数据分析数据分析这是一个追溯的回顾.

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